Improvements in robotic technologies has increased the level of automation in many industries. From the automobile industry to the semiconductor manufacturing industry, robotic technology has automated many of the repetitive tasks formerly performed by humans. A benefit of the mechanical automation is the precision achievable by computer-controlled automated systems. For automated alignment or operational robotic systems, the programming of such robots is typically extensive, with much of the physical processing of the automated systems tied to the precise locations and measurements of the automated system and the objects on which it operates.
In order to maintain precision, an automated alignment system is usually either (a) locked into a rigid positional frame of reference or (b) capable of “seeing” the objects and adjusting its positioning and processing to the objects' orientation. Because maintaining a rigid frame of reference as a sole imaging or alignment method typically requires considerable effort, “sight”-automated systems, which typically have a combination of a fixed frame of reference and sighting means, are generally more reliable and economical to employ.
One successful method for building a “sight”-automated system has been to provide an automated system, such as an autochanger for large-scale computer storage, with an illumination source and optical sensing components. Imaging targets are typically affixed to the objects to provide a reflection point for the illumination source and image sensors of the system. The imaging targets are normally white in order to maximize the contrast between the background equipment and the target. As the illumination source shines or radiates over the white imaging target, optical sensors pick up the change in the reflected light based on the large contrast between the target and the background. In some applications, the imaging targets may also include bar codes, thereby providing an intelligence to the optical sensing.
Still other applications may take advantage of a combination of both plain imaging targets and bar codes. Such systems use the plain imaging target to align with the object. The optical sensors are then generally able to read the bar code to determine whether the object is the correct target object. Furthermore, the bar codes may provide an initial reference to the automated system that indicates a general area of the system to which the automated sensor must generally move.
For example, multiple tapes of electronic information may be stored in magazines cataloged by bar code and stacked in racks or shelves. Each shelving unit generally has an imaging target used by the automated system to pinpoint different locations on the shelf. In such systems, a single illumination source and optical sensor is used to lock onto both the imaging target and the bar codes. This combination generally simplifies the design of the automated system and reduces operating costs. However, problems generally arise as the illumination source is positioned farther from the imaging target. Because only a single illumination source and optical sensor are used to image both elements, it may be positioned in such a manner to image one element more easily than the other or in such a manner to read both elements with the same, but non-optimal, difficulty. In typical embodiments, the illumination source and optical sensors are normally positioned to provide accurate reading of each individual tape's bar code. Thus, the greater distance between the illumination source and the general imaging target may sometimes cause failed or inaccurate detection by the optical sensing device. This problem could be alleviated by manufacturing a dual illumination source and optical sensor, or by increasing the size and intensity of the illumination source and/or the size and sensitivity of the optical sensor. However, both of these options add cost and complexity to the automated systems.
Furthermore, the white imaging targets frequently fail to provide adequate return radiation to register on the optical sensor. This failure may be caused by a background material that is glossy or shiny, creating a reflection comparable to the white imaging target. The failure to may also be caused by the particular shape of the object at the point on which the imaging target is affixed. If the object's facing is curved or angles away from the illumination source, the optical sensor may not register sufficient light reflection or contrast from the imaging target.